Chris Bahnsen

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About

Chris Bahnsen is a leading researcher in the automation of critical infrastructure inspection, with a primary focus on sewer systems. His work bridges computer vision, deep learning, and robotics to transform slow, labor-intensive manual inspection processes into efficient, automated systems. Bahnsen’s major contributions include pioneering the use of 3D sensors for sewer inspection—his 2021 review paper, cited 38 times, provides a quantitative framework for evaluating sensor technologies in this challenging environment. He also developed deep convolutional neural networks for water level estimation in sewer pipes (2020, 22 citations), enabling real-time, data-driven assessments that reduce human error. These contributions address both economic and scientific needs, offering utilities a path to optimize maintenance schedules and replacement planning. Bahnsen’s work is notable for its practical impact on infrastructure resilience, directly tackling the bottleneck of manual video review by operators. His research stands out for its integration of advanced sensing and AI to solve real-world problems in urban water management, making him a key figure in the push toward smarter, more reliable infrastructure systems.